Sebastian Müller

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Hey all (and thanks @javoha form mentioning), sorry for being late to the Party. Sebastian here, Core-Developer from [GeoStat-Framework](https://github.com/GeoStat-Framework) and [GSTools](https://github.com/GeoStat-Framework/GSTools). What about a collaboration? We provide kriging and (conditioned)...

Exactly same here.

I was thinking about bringing the models of PyKrige in line with the ones from [GSTools](https://github.com/GeoStat-Framework/GSTools). There the length scale in the exponential model coincides with its integral scale.

We could also introduce a scaling factor, that is fixed (not estimated during the variogram fitting). This could also help in the future to automatically determine a search radius (See...

This is solved in GSTools with the introduction of the `rescale` argument, that will be used by PyKrige in the future: - https://github.com/GeoStat-Framework/GSTools/pull/109

We should use the properties of the kriging matrix to optimize that. The kriging equation can always be reformulated to use the covariance-matrix instead of the semi-variogram-matrix (as done now)....

Hey @jonathf! This sounds like a good idea for a work-together! in PyKrige, you can provide a list of callable drift functions for Universal kriging. This is also possible in...

If you want to fit the coefficients of the polynomials during kriging, Universal-Kriging is the right choice. If the coefficients are fitted beforehand, you should subtract the trend from the...

@jonathf > The paper defines the kriging term of the equation as `\sigma^2 Z(x)` where `Z(x)` is zero mean, unit variance and stationary Gaussian process, and `\sigma^2` is a Kriging...